Rapid Determination of Free Fatty Acids in Poultry Feed Lipid Extracts by SB-ATR FTIR Spectroscopy
Bibliographic record
Abstract
A simple, rapid, and reproducible method has been developed for the quantitative determination of free fatty acid (FFA) content in lipids extracted from poultry feeds by Fourier transform infrared (FTIR) spectroscopy with the use of a single-bounce attenuated total reflectance (SB-ATR) accessory. An FTIR calibration curve was prepared by gravimetrically adding oleic acid (15-37%) to pure refined, bleached, and deodorized (RBD) canola oil and measuring the area of the COOH absorption band at 1710 cm-1. The oil from each of 12 poultry feed formulations was extracted using conventional Soxhlet extraction, and after evaporation of the solvent, the FFA content was determined by the conventional AOCS titrimetric procedure and by the SB-ATR/FTIR method. The SB-ATR/FTIR FFA predictions were related to those determined by the AOCS titrimetric method by linear regression, producing an R value of 0.999 and a SD of +/-0.28% FFA. Time-course spectra collected as lipids extracted into hexane indicated that a 15 min extraction was adequate to obtain a representative sample for FFA determination, with further extraction resulting in little, if any, change in the proportion of FFA in the lipid extract. Only a small volume of the hexane extract ( approximately 20 mL) yielded sufficient material for the SB-ATR/FTIR analysis. Thus, by shortening the extraction time and taking a small sample so as to reduce solvent removal time, the SB-ATR/FTIR procedure provides a very simple and rapid means of determining the FFA content of poultry feed lipids.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".